Birleşik Krallık'taki Ticari Bankaların Performanslarının Gri İlişki Analizi Kullanarak İncelenmesi

Yıl 2024, Cilt: 39 Sayı: 4, 1079 - 1106

Isik Akin

https://doi.org/10.24988/ije.1396460

Öz

Bu çalışma, Birleşik Krallık bankacılık sistemindeki ticari bankaların mali performansını Gri İlişki Analizi'ni kullanarak değerlendirmektedir. Çalışmanın temel amacı, bankaların performansını etkileyen önemli göstergeleri belirlemektir. Bu göstergelerin belirlenmesi, bankaların stratejilerini belirlemesine, güçlü yönlerinden faydalanmasına, zayıflıklarını ele almasına, dinamik piyasalarda dayanıklılıklarını ve karlılıklarını paydaşlar için güvence altına almalarına yardımcı olur. 2020 ile 2022 yılları arasındaki veriler kullanılarak, karlılık, faiz oranı, likidite ve fonlar, varlık kalitesi ve sermaye yeterliliği olmak üzere beş kategori analiz edilmiştirBu dönem, İngiltere'deki bankaların performansı üzerinde Covid-19'un etkisini ortaya koymak amacıyla seçildi. Barclays plc, güçlü finansal yönetim sergileyen ve en iyi performans gösteren bankalar arasında ön plana çıkmaktadır. Nationwide Building Society, varlık kalitesi ve fonlama alanında istikrarlı bir performans sergilemektedir. Lloyds Banking Group, iyi karlılık ve sermaye yeterliliği ile istikrar gösterir. Santander UK plc dalgalı bir performansa sahiptir. NatWest Group plc orta düzeyde dalgalanmalar gösterirken, HSBC Holding plc ve Standard Chartered plc belirli zorluklarla karşı karşıyadır. Bu çalışmanın sonucuna göre, Gri İlişki Analizi (GRA), stratejik kararlar ve risk yönetimine yardımcı olan kullanışlı bir araçtır. Karlılık, istikrarı ve performansı destekleyerek bankacılık sektörüne fayda sağlamaktadır. Etkin faiz oranı yönetimi, piyasa dalgalanmaları sırasında istikrarı sağlayan önemli bir faktördür. Yüksek varlık kalitesi, banka performansını güçlendirirken, etkili likidite yönetimi ise bankaların sürekli başarısı için hayati öneme sahiptir.

Anahtar Kelimeler

Ticari Bankalar, Performans Değerlendirmesi, Gri İlişki Analizi, Finansal Göstergeler, Birleşik Krallık Bankacılık Sistemi

Investigating Performances of Commercial Banks in the UK by Using Grey Relation Analysis

Öz

This study employs Grey Relational Analysis to assess the financial performance of commercial banks in the UK banking system. The main aim of the study is to identify influential indicators that have an impact on the banks’ performance. Identifying influential indicators helps banks determine strategies, capitalize on strengths, address weaknesses, and assure stakeholders of their resilience and profitability in dynamic markets. Using data from 2020 to 2022, five categories—profitability, interest ratio, liquidity and funds, asset quality, and capital adequacy—were analysed. This period was chosen to reveal the impact of Covid-19 on the performance of banks in the UK. Barclays plc consistently emerges as a top performer, showcasing robust financial management. Nationwide Building Society maintains stable performance with strengths in asset quality and funding. Lloyds Banking Group demonstrates stability with good profitability and capital adequacy. Santander UK plc exhibits fluctuating performance. NatWest Group plc shows moderate fluctuations, while HSBC Holding plc and Standard Chartered plc face specific challenges. According to the results of this study, Grey Relational Analysis (GRA) is a useful tool that aids strategic decision-making and risk management. It benefits the banking sector by supporting profitability, stability, and performance. Effective interest rate management is a significant factor in maintaining stability during market fluctuations. High asset quality strengthens bank performance, while efficient liquidity management is crucial for the sustained success of banks.

Anahtar Kelimeler

Commercial Banks, Performance Evaluation, Grey Relational Analysis, Financial Indicators, UK Banking System

Kaynakça

• Abedifar, P., Molyneux, P. and Tarazi, A. (2018). Non-interest income and bank lending. Journal of Banking and Finance, 87, 411-426. https://doi.org/10.1016/j.jbankfin.2017.11.003
• Ahn, H. and Le, M. H. (2014). An insight into the specification of the input-output set for DEA-based bank efficiency measurement. Management Review Quarterly, 64(1), 3-37. https://doi.org/10.1007/s11301-013-0098-9
• Alkhazaleh, A. M. K. (2017). Does banking sector performance promote economic growth? Case study of Jordanian commercial banks. Problems and Perspectives in Management, 15(2), 55-66. https://www.ceeol.com/search/article-detail?id=620327
• Allen, F. (2004). the Efficiency and Stability of Banks and Markets. National Bank of Belgium Working Paper, (52). https://ssrn.com/abstract=1691591
• Allen, F., Carletti, E., and Gu, X. (2008). The roles of banks in financial systems. Oxford handbook of banking, 32-57. https://shorturl.at/fRkPO
• Aspal, P. K. and Dhawan, S. (2014). Financial performance assessment of banking sector in India: A case study of old private sector banks. The Business and Management Review, 5(3), 196. https://shorturl.at/RJeTh
• Bhattarai, P. (2018). Effect of Non-Performing Loan on Profitability of Nepalese Commercial Banks (Doctoral dissertation, Department of Management). https://elibrary.tucl.edu.np/handle/123456789/1148
• Barclays (2023). Our Story. https://home.barclays/who-we-are/our-history/
• Chang, S. C. and Tsai, P. H. (2016). A hybrid financial performance evaluation model for wealth management banks following the global financial crisis. Technological and Economic Development of Economy, 22(1), 21-46. https://doi.org/10.3846/20294913.2014.986771
• De la Torre, A., Pería, M. S. M. and Schmukler, S. L. (2010). Bank involvement with SMEs: Beyond relationship lending. Journal of Banking and Finance, 34(9), 2280-2293. https://doi.org/10.1016/j.jbankfin.2010.02.014
• Deng, J. L. (1982). The Control problem of grey systems. System and Control Letter. https://doi.org/10.1016/S0167-6911(82)80025-X
• Dogan, M. (2013). Measuring bank performance with grey relational analysis: the case of Turkey. Ege Academic Review, 13(2), 215-226. https://dergipark.org.tr/en/download/article-file/559830
• Fallah, M., Aryanezhad, M., Najafi, S. and Shahsavaripour, N. (2011). An empirical study on measuring the relative efficiency using DEA method: A case study of bank industry. Management Science Letters, 1(1), 49-56. https://rb.gy/m1fnzp
• Fazeli, Z., Bikzadeh Abbasi, F., and Sardar, S. (2023). Identifying and Ranking Indicators Affecting the Evaluation of Financial Performance in Private Banks using the Fuzzy AHP Method. Fuzzy Optimization and Modeling Journal, 4(3), 40-53. https://doi.org/10.30495/fomj.2023.1995996.1114
• Feng, C. M. and Wang, R. T. (2000). Performance evaluation for airlines including the consideration of financial ratios. Journal of Air Transport Management, 6(3), 133-142. https://doi.org/10.1016/S0969-6997(00)00003-X
• Fitch Solutions (2024). Fundamental Financial Data: Bank Financial Data. https://www.fitchsolutions.com/credit/fundamental-data
• Gambacorta, L. and Karmakar, S. (2016). Leverage and risk-weighted capital requirements. https://ssrn.com/abstract=2849574
• Guru, S. and Mahalik, D. K. (2019). A comparative study on performance measurement of Indian public sector banks using AHP-TOPSIS and AHP-grey relational analysis. Opsearch, 56(4), 1213-1239. https://doi.org/10.1007/s12597-019-00411-1
• Hashemi, S. H., Karimi, A. and Tavana, M. (2015). An integrated green supplier selection approach with analytic network process and improved Grey relational analysis. International Journal of Production Economics, 159, 178-191. https://doi.org/10.1016/j.ijpe.2014.09.027
• Ho, C. T. (2006). Measuring bank operations performance: an approach based on Grey Relation Analysis. Journal of the Operational Research Society, 57(4), 337-349. https://doi.org/10.1057/palgrave.jors.2601985
• HSBC (2023). About HSBC. https://www.about.hsbc.co.uk/
• Huang, S. J., Chiu, N. H. and Chen, L. W. (2008). Integration of the grey relational analysis with genetic algorithm for software effort estimation. European Journal of Operational Research, 188(3), 898-909. https://doi.org/10.1016/j.ejor.2007.07.002
• Ikram, M., Sroufe, R., Rehman, E., Shah, S. Z. A. and Mahmoudi, A. (2020). Do quality, environmental, and social (QES) certifications improve international trade? A comparative grey relation analysis of developing vs. developed countries. Physica A: Statistical Mechanics and its Applications, 545, 123486. https://doi.org/10.1016/j.physa.2019.123486
• Ilahi, I., Jamil, R. A. and Kazmi, S. (2014). Financial performance of investment banks: a comparison. Journal of Management Info, 4(1), 35-51. https://readersinsight.net/jmi/article/view/20/pdf_14
• Karlan, D. and Morduch, J. (2010). Access to finance. In Handbook of development economics (Vol. 5, pp. 4703-4784). Elsevier. https://doi.org/10.1016/B978-0-444-52944-2.00009-4
• Kula, V., Kandemir, T., and Baykut, E. (2016). An Investigation of Financial Performances of Insurance Companies and Pension Fund Trading Borsa Istanbul with Grey Relational Analyze. Journal of Economics and Administrative Sciences Dergisi, 18(1). https://doi.org/10.5578/jeas.26489
• LaPlante, A. E. and Paradi, J. C. (2015). Evaluation of bank branch growth potential using data envelopment analysis. Omega, 52, 33-41. https://doi.org/10.1016/j.omega.2014.10.009
• Li, L. and Wang, F. (2010). Grey Relational Analysis on the Effect Evaluation of Cooperation between Banks and Securities Companies. In 2010 Third International Conference on Knowledge Discovery and Data Mining (pp. 577-580). IEEE. https://doi.org/10.1109/WKDD.2010.151
• Liu, H. and Liu, Y. (2023). Colleges’ performance assessment of university based on grey relational analysis. Journal of Intelligent and Fuzzy Systems, (Preprint), 1-10. https://doi.org/10.3233/JIFS-223286
• Liu, H. C., Wang, L. E., You, X. Y. and Wu, S. M. (2019). Failure mode and effect analysis with extended grey relational analysis method in cloud setting. Total Quality Management and Business Excellence, 30(7-8), 745-767. https://doi.org/10.1080/14783363.2017.1337506
• Lloyds Banking Group (2023). Who we are. https://www.lloydsbankinggroup.com/who-we-are.html
• Malik, F. A. and Malik, H. A. (2022). An analysis of ways to strengthen financial system in developing Indian economy. Shanlax International Journal of Management, 9(3), 41-44. https://shorturl.at/1y2k5
• Mamun, M. A. (2013). Performance evaluation of prime bank limited in terms of capital adequacy. Global Journal of Management and Business Research, 13(9), 26-29. https://shorturl.at/TpFXE
• Maradin, D., Drazenovic, B. O. and Benkovic, S. (2018). Performance evaluation of banking sector by using DEA method. Economic and Social Development: Book of Proceedings, 684-690. https://rb.gy/6tv3d3
• Margasova, V., Muravskyi, O., Vodolazska, O., Nakonechna, H., Fedyshyn, M. and Dovgan, L. (2019). Commercial Banks as a Key Element in Regulating Cash Flows in the Business Environment. International Journal of Recent Technology and Engineering, 8(4), 4537-4543. https://doi.org/10.35940/ijrte.D8465.118419
• Mashamba, T. (2018). The effects of Basel III liquidity regulations on banks’ profitability. Journal of governance and regulation, (7, Iss. 2), 34-48. http://ir.gzu.ac.zw:8080/jspui/handle/123456789/237
• Mbekomize, C. J. and Mapharing, M. (2017). Analysis of determinants of profitability of commercial banks in Botswana. International Journal of Academic Research in Accounting, Finance and Management Sciences, 7(2), 131-144. http://dx.doi.org/10.6007/IJARAFMS/v7-i2/2878
• Meng, Y. H., Guo, H. L. and Hu, B. (2013). Grey relational analysis on service innovation performance in commercial banks. In 2013 10th International Conference on Service Systems and Service Management (pp. 35-40). IEEE. https://doi.org/10.1109/ICSSSM.2013.6602583
• Menicucci, E. and Paolucci, G. (2016). Factors affecting bank profitability in Europe: An empirical investigation. African Journal of Business Management, 10(17), 410-420. https://doi.org/10.5897/AJBM2016.8081
• Messai, A. S. and Jouini, F. (2013). Micro and macro determinants of non-performing loans. International journal of economics and financial issues, 3(4), 852-860. https://rb.gy/dux6i5
• Naser, N. (2019). The Interaction between Profitability and Macroeconomic Factors for Future Examinations of European Banks Soundness–Theoretical Study. https://core.ac.uk/download/pdf/324266876.pdf
• Nationwide Building Society (2023). About us. https://www.nationwide.co.uk/about-us/
• NatWest Group (2023). Our Brands. https://www.natwestgroup.com/who-we-are/our-brands/natwest.html
• Nazeri, A., and Keshavarzi, M. (2019). Assessing the Performance of Branches of Refah Bank in Tehran Province by Combining Analytic Hierarchy Process (AHP) and Data Envelopment Analysis (DEA) Algorithms in Fuzzy Conditions. International journal of industrial engineering and operational research, 1(1), 11-27. https://shorturl.at/ypjKL
• Ozcelik, F., and Ozturk, B. A. (2014). Evaluation of Banks' Sustainability Performance in Turkey with Grey Relational Analysis. Journal of Accounting and Finance (63). https://rb.gy/xpjvh3
• Pan, W. T., and Leu, Y. (2016). An analysis of bank service satisfaction based on quantile regression and grey relational analysis. Mathematical Problems in Engineering, 2016. https://doi.org/10.1155/2016/1475148
• Sahyouni, A., and Wang, M. (2019). Liquidity creation and bank performance: evidence from MENA. ISRA International Journal of Islamic Finance, 11(1), 27-45. https://doi.org/10.1108/IJIF-01-2018-0009
• Sakinc, I., and Gülen, M. (2014). The performance comparison of the participation banks acting in Turkey via the grey relations analysis method. Journal of Economic and Social Thought, 1(1), 3-14. https://hdl.handle.net/10419/105838
• Salike, N., and Ao, B. (2018). Determinants of bank’s profitability: role of poor asset quality in Asia. China Finance Review International, 8(2), 216-231. https://doi.org/10.1108/CFRI-10-2016-0118
• Santander UK (2023). About Santander UK. https://www.santander.co.uk/about-santander
• Sarraf, F., and Nejad, S. H. (2020). Improving performance evaluation based on balanced scorecard with grey relational analysis and data envelopment analysis approaches: Case study in water and wastewater companies. Evaluation and program planning, 79, 101762. https://doi.org/10.1016/j.evalprogplan.2019.101762
• Sharipova, N. D., and Asadova, S. D. (2023). The Role of Banks in the Modern Monetary System. Procedia of Theoretical and Applied Sciences, 6, 55-62. http://eprints.umsida.ac.id/11531/
• Silaban, P. (2017). The effect of capital adequacy ratio, net interest margin and non-performing loans on bank profitability: The Case of Indonesia. https://www.um.edu.mt/library/oar//handle/123456789/43353
• Standard Charted (2023). We’re here for good. https://www.sc.com/uk/about/
• Suvvari, A., and Goyari, P. (2019). Financial performance assessment using Grey relational analysis (GRA) An application to life insurance companies in India. Grey Systems: Theory and Application, 9(4), 502-516. https://doi.org/10.1108/GS-05-2019-0010
• Unvan, Y. A. (2020). Financial performance analysis of banks with TOPSIS and fuzzy TOPSIS approaches. Gazi University Journal of Science, 33(4), 904-923. https://doi.org/10.35378/gujs.730294
• Wruuck, P., Schildbach, J., AG, D. B., and Hoffmann, R. (2015). Promoting investment and growth: The role of development banks in Europe. Deutsche Bank Research. https://rb.gy/95noh6
• Wu, C. R., Lin, C. T., and Tsai, P. H. (2010). Evaluating business performance of wealth management banks. European journal of operational research, 207(2), 971-979. https://doi.org/10.1016/j.ejor.2010.04.034
• Zhu, R., Bhutta, Z. M., Zhu, Y., Ubaidullah, F., Saleem, M., and Khalid, S. (2022). Grey relational analysis of country-level entrepreneurial environment: A study of selected forty-eight countries. Frontiers in Environmental Science, 10, 985426. https://doi.org/10.3389/fenvs.2022.985426